ORIGINAL ARTICLE

QTL mapping of mandarin (Citrus reticulata) fruit charactersusing high-throughput SNP markers

Yuan Yu1& Chunxian Chen2

& Frederick G. Gmitter Jr.1

Received: 11 April 2016 /Revised: 21 June 2016 /Accepted: 1 July 2016 /Published online: 18 July 2016# Springer-Verlag Berlin Heidelberg 2016

Abstract Seedlessness, flavor, and color are top priorities formandarin (Citrus reticulata Blanco) cultivar improvement.Given long juvenility, large tree size, and high breeding cost,marker-assisted selection (MAS) may be an expeditious andeconomical approach to these challenges. The objectives ofthis study were to construct high-density mandarin geneticmaps and to identify single nucleotide polymorphism (SNP)markers associated with fruit quality traits. Two parental ge-netic maps were constructed from an F1 population derivedfrom ‘Fortune’ × ‘Murcott’, two mandarin cultivars with dis-tinct fruit characters, using a 1536-SNP Illumina GoldenGateassay. The map for ‘Fortune’ (FOR) consisted of 189 SNPsspanning 681.07 cM and for ‘Murcott’ (MUR) consisted of106 SNPs spanning 395.25 cM. Alignment of the SNP se-quences to the Clementine (Citrus clementina) genomeshowed highly conserved synteny between the genetic mapsand the genome. A total of 48 fruit quality quantitative traitloci (QTLs) were identified, and ten of them stable over two or

more samplings were considered as major QTLs. A cluster ofQTLs for flavedo color space values L, a, b, and a/b and juicecolor space values a and a/bwere detected in a single genomicregion on linkage group 4. Two carotenoid biosynthetic path-way genes, pds1 and ccd4, were found within this QTL inter-val. Several SNPs were potentially useful in MAS for thesefruit characteristics. QTLs were validated in 13 citrus selec-tions, which may be useful in further validation and tentativeMAS in mandarin fruit quality improvement.

Keywords Mapping . Fruit quality .Mandarin . Breeding

Introduction

Sweet oranges (Citrus sinensis L. Osb.), mandarins (Citrusreticulata, commonly referred to as tangerines in the USA),and grapefruit (Citrus paradisi Macf.) are among the mostimportant fruit commodities in the USA. The production andconsumption of fresh mandarin fruits have been continuouslyincreasing due to their desirable attributes, including ease ofpeeling, pleasant aroma and flavor, and high vitamin C andcarotenoid content (Baldwin and Jones 2013). From 2013 to2015, the annual production and value of mandarin in theUSA increased, f rom 682,000 to 843,000 t and$426,101,000 to $513,932,000, respectively. Fresh fruit con-sumption accounted for 84.7 % of the total production in2015; coincidentally, the production and value of orangesand grapefruit both decreased due to citrus greening diseaseand changing consumer preferences (http://usda.mannlib.cornell.edu/usda/current/CitrFrui/CitrFrui-09-17-2015.pdf).

Awareness of health benefits from some phytonutrients,i.e., carotenoids, particularly in mandarin fruit, is increasinglybecoming a driver of purchase and consumption. Aroma vol-atiles and carotenoids are two major interrelated components

Communicated by W.-W. Guo

Electronic supplementary material The online version of this article(doi:10.1007/s11295-016-1034-7) contains supplementary material,which is available to authorized users.

* Frederick G. Gmitter, Jr.fgmitter@ufl.edu

Yuan Yuymmzyz@ufl.edu

Chunxian ChenChunxian.Chen@ars.usda.gov

1 Citrus Research and Education Center, University of Florida, LakeAlfred, FL 33850, USA

2 Southeastern Fruit and Tree Nut Research Laboratory, ARS, USDA,Byron, GA 31008, USA

Tree Genetics & Genomes (2016) 12: 77DOI 10.1007/s11295-016-1034-7

that determine mandarin fruit flavors and colors (Tietel et al.2011). Improvement in seedlessness, flavor, and color ranksamong the high priorities of the breeding goals for Floridamandarin cultivars. Citrus conventional breeding is costlyand challenging, and hybrids usually take 5 years or more tobear fruits. The large tree size also restricts the capacity togrow hybrid populations for selection of superior individuals.Molecular markers could be a potentially useful solution tothese challenges in citrus breeding (Gmitter et al. 2007). Themarker-assisted selection (MAS) approach can help cull prog-eny seedlings with poor performance potential at an earlystage, and markers linked to mandarin fruit quality traits canfacilitate genetic improvement and accelerate the release ofsuperior mandarin cultivars.

Compared to crops and vegetables, genetic mapping incitrus, especially in mandarin, remains limited. Most geneticmapping studies in citrus were performed in populations usu-ally involving trifoliate orange (Poncirus trifoliata) because ofits disease resistance and cold tolerance for rootstock breeding(Chen et al. 2008). In the 1990s, without available citrus ge-nomic sequence information, different types of dominantDNA markers were developed and even now are still utilizedfor citrus genetic mapping studies. Those dominant markersincluded random amplified polymorphic DNA (RAPD)(Cristofani et al. 1999; Sahin-Cevik and Moore 2012; Caiet al. 1994), amplified fragment length polymorphism(AFLP) (de Oliveira et al. 2007), and inter-simple sequencerepeat (ISSR) (Sankar and Moore 2001; Gulsen et al. 2010;Kijas et al. 1997; Roose et al. 2000). In addition, more pow-erful co-dominant markers were added to citrus genetic map-ping studies such as restriction fragment length polymorphism(RFLP) (Durham et al. 1992; Jarrell et al. 1992) and cleavedamplified polymorphic sequences (CAPS) (Garcia et al.1999). With broad international collaboration, abundant sim-ple sequence repeat (SSR) marker sets have been developedfrom citrus expressed sequence tags (ESTs) and genome se-quences and used for genetic map construction for trifoliateorange (Chen et al. 2008; Ruiz and Asins 2003), sweet orange(Chen et al. 2008), mandarin (Gulsen et al. 2010), and pum-melo (Citrus maxima) (Bernet et al. 2010). High-throughputmolecular markers and assays were required for genome-wideassociation and linkage mapping studies. Citrus single nucle-otide polymorphisms (SNPs) were initially mined and validat-ed from mass citrus expressed sequence tags (ESTs) (Chenand Gmitter 2013). A GoldenGate SNP assay was then devel-oped, including 1536 well-characterized, evenly distributedSNPs that were based on sweet orange bacterial artificial chro-mosome (BAC) end sequences and high-coverage whole-ge-nome shotgun reads used to assemble the sweet orange ge-nome (Wu et al. 2014). A Clementine reference genetic map(961 markers for 1084.1 cM) was constructed using BAC endsequence-derived SNPs and EST SSRs and insertion/deletion(indel) markers and used to assist the Clementine whole-

genome sequence assembly (Ollitrault et al. 2012b; Ollitraultet al. 2012a; Wu et al. 2014).

In addition to genetic map construction, molecularmarkers/quantitative trait loci (QTLs) have been associatedwith citrus disease resistance and stress tolerance, such asresistances to citrus tristeza virus (CTV) (Gmitter Jr et al.1996), nematodes (Ling et al. 2000), citrus variegated chloro-sis (CVC) (Oliveira et al. 2002), Alternaria (Dalkilic et al.2005), and citrus leprosis virus (CiLV) (Bastianel et al.2009); tolerances to low temperature (Cai et al. 1994); Na+

and Cl− stress (Tozlu et al. 1999b); salinity (Tozlu et al.1999a); and freezing (Weber et al. 2003). Moreover, severalgenetic mapping studies have been performed on citrus fruitcharacteristics, including fruit acidity (Fang et al. 1997), seednumber and yield (García et al. 2000), fruit size and segmentnumber (Sahin-Cevik and Moore 2012), fruit setting (Gulsenet al. 2011), carotenoid content (Sugiyama et al. 2011;Sugiyama et al. 2014), and seed reproductive traits (Ragaet al. 2012). Reports of genetic mapping of citrus fruit char-acters remain very scarce, largely restrained by the lack ofphenotypical data and the complexity of those traits.

In this paper, we report the construction of genetic mapsusing a mandarin F1 population of ‘Fortune’ × ‘Murcott’ andthe identification of molecular markers and candidate geneslinked to mandarin fruit quality traits. The flanking markersand candidate genes identified may be applied in MAS formandarin breeding. ‘Fortune’ was reported previously to bea hybrid of Clementine × ‘Dancy’mandarin (Furr 1964); how-ever, recent studies using molecular markers excluded‘Dancy’ as the pollen parent but indicated ‘Orlando’ tangeloas the likely pollen parent (Barry et al. 2014). ‘Murcott’, themost widely grown late-maturing mandarin in Florida, is be-lieved to be a hybrid of mandarin and sweet orange (Hodgson1967). ‘Fortune’ and ‘Murcott’ produce fruit with contrastingqualities. ‘Fortune’ produces fruit that are medium tomedium-large in size, moderately oblate shape, with reddish-orange-colored rind and orange-colored pulp, slightly acidic, andweakly aromatic, while ‘Murcott’ fruits are medium in size,oblate to subglobose in shape, with a yellowish-orange-colored rind but deep orange-colored pulp, tender and juicy,fine texture, sweet, and with a very rich flavor (Hodgson1967; Aleza et al. 2010).

Materials and methods

Citrus cultivars, selections, and F1 hybrids

Mandarins ‘Fortune’, ‘Murcott’, and their 116 F1 hybrids wereplanted in 1991 for breeding purposes and used in this re-search. Eleven additional citrus selections used in this studyinclude ‘Goutou’ sour orange, ‘King’mandarin, ‘Moro’ bloodorange, ‘Nules’ Clementine, ‘Owari’ Satsuma, ‘Pimpled’

77 Page 2 of 16 Tree Genetics & Genomes (2016) 12: 77

mandarin, ‘Ponkan’ mandarin, ‘Rangpur’ lime, a standardsour orange, ‘Sunki’ mandarin, and ‘Zhuluan’ sour orange.‘Moro’ blood orange and ‘Sunki’ mandarin were grown inthe Florida Citrus Arboretum at Winter Haven; all other citrusselections and F1 hybrids were grown in the University ofFlorida Citrus Research and Education Center (UF-CREC)groves under the same field soil, irrigation, illumination, andnutrition conditions.

Trait evaluation

Fruits free of any peel defects from ‘Fortune’, ‘Murcott’, andF1 hybrids were randomly harvested twice each season in theircommercial maturity condition (identical to industry harvesttime) in 2012 and 2013, respectively. The ‘Fortune’ fruitswere harvested in December and January, and the ‘Murcott’fruits were picked in February and March. The fruits of F1progeny were harvested twice in an interval of 1 month de-pending on maturity from December to April. In order tosimplify later analysis, all fruit samples from ‘Fortune’,‘Murcott’, and F1 hybrids harvested from the first and secondsamplings each year were recorded as January and February,respectively. All other citrus selections were harvested once intheir commercial maturity condition in the 2014 harvest sea-son. Fruits were harvested in the grove and taken immediatelyto the lab for phenotypic evaluation. According to the methodsdescribed byMiyazaki et al. (Miyazaki et al. 2011), fruits weresoaked in 16 L warm water solution containing 200 mL de-tergent (DECCO 241 Fruit and Vegetable Kleen, Monrovia,CA, USA), washed for about 30 s, and rinsed. Then, the fruitswere sanitized in 10 L 100-ppm peroxyacetic acid solution at30 to 35 °C (Biosafe System, East Hartford, CT, USA) for3 min.

A total of 15 fruits from each accession were used to mea-sure flavedo color, fruit diameter (FD, in mm), and fruitweight (FW, in g) individually. Fruit flavedo color was mea-sured using a Minolta CR-331 colorimeter (Minolta Corp.,Ramsey, NJ, USA) on three random locations around theequatorial plane of fruit. Color measurement score was de-scribed as Hunter color space value: L (FCL, black to white),

a (FCA, green to red), b (FCB, blue to yellow), and a over bratio (FCAB) (Table 1).

After measurement of those external fruit characteristics,the 15 fruits from each tree were grouped into three pools withfive fruits per pool, manually peeled, and juiced using a com-mercial citrus juicer (Hamilton Beach, Southern Pines, NC,USA). Then, each fruit juice pool as one biological replicatewas used to count, measure, and/or calculate seed number(SD), juice percentage (JP, in ml/100 g), juice color, solublesolid content (SSC, in g/100 mL), and titratable acidity (TA, ing/100 mL, presented as percentage of citric acid). Accordingto the method described by Fanciullino et al. (Fanciullino et al.2008), an aliquot (8 mL) of each juice sample was put in aplate (diameter of 5 cm) in a sealed container (provided withthe colorimeter) and measured using the Minolta CR-331 col-orimeter. Juice color measurement score was also described asHunter color space value, including L (JCL), a (JCA), b(JCB), and a over b ratio (JCAB). SSC was measured usinga Leica 10430 hand-held refractometer (Leica Inc., Buffalo,NY, USA). TA was determined by titration with 0.1 mol/Lsodium hydroxide (NaOH) solution to pH 8.2. SSC over TAratio (ST) represented the calculated SSC/TA ratio. SD wascalculated by dividing the number of seeds in each fruit poolby the number of fruits in the pool. JP was calculated bydividing juice volume of each juice pool by the overall weightof fruits in the pool.

Descriptive statistical analysis

JMP Pro 10 (SAS Corporation, Cary, NC, USA) wasemployed to analyze the fruit phenotypic data. The mean val-ue, minimum, maximum, standard deviation, kurtosis, andskewness were calculated for parents and/or F1 progeny. Inaddition, Pearson correlation coefficients of fruit traits overfour samplings (January and February in 2012 and 2013) werecalculated. The Shapiro-Wilk test (Shapiro and Wilk 1965)was applied to test normality of trait distributions. The analy-sis of variance (ANOVA) test was performed to test for differ-ences of phenotypic data from citrus selections.

Table 1 List of abbreviations formandarin fruit traits Abbreviation Fruit trait Abbreviation Fruit trait

FCA Flavedo color space value a JCB Juice color space value b

FCAB Flavedo color space value a/b JCL Juice color space value L

FCB Flavedo color space value b JP Juice percentage

FCL Flavedo color space value L SD Seed number

FD Fruit diameter SSC Soluble solids content

FW Fruit weight ST Soluble solids content: titratable acidity

JCA Juice color space value a TA Titratable acidity

JCAB Juice color space value a/b

Tree Genetics & Genomes (2016) 12: 77 Page 3 of 16 77

Genomic DNA extraction and SNP genotyping

Genomic DNA was extracted from fresh leaves using theCTAB method according to Aldrich and Cullis (1993) andused to genotype the parents and hybrids using theGoldenGate array platform in the University of Florida’sInterdisciplinary Center for Biotechnology Research (UF-ICBR). DNA samples for two parents were replicated twicein each plate. Genotyping data were collected and analyzed bythe Genome Studio software (Illumina Inc., San Diego, CA,USA). All SNPs were blasted against the Clementine genomeV1.0 (http://www.phytozome.net), and the physical positionsof SNPs on corresponding scaffolds of the Clementinegenome were obtained. All SNPs were named from m1 to m1536, followed by ‘-s’ and an Arabic number, whichcorresponded to the Clementine genome scaffold.

Linkage analysis and map construction

Following the coding scheme of JoinMap cross pollinator(CP) population mode, SNPs were coded for the three segre-gation types, markers heterozygous only in female parent‘Fortune’ (lmxll), only in male parent ‘Murcott’ (nnxnp),and in both parents (hkxhk). In order to ensure genetic mapquality, any SNP was excluded from the final mapping set if it(1) had more than 20 missing calls, (2) was homozygous intwo parents, and (3) was not segregating in F1 progeny.

Linkage maps were constructed for the two highly hetero-zygous parents using JoinMap 4.1 (Van Ooijen 2006, 2011b)and the two-way pseudo-testcross strategy (Chen et al. 2008;Ollitrault et al. 2012a; Ritter et al. 1990). First, the <lmxll>and <nnxnp> type SNPs were imported for maternal and pa-ternal map construction using JoinMap under the backcrosspopulation mode. Next, these markers were tested by χ2

(α = 0.05) to the Mendelian segregation ratio 1:1.Framework maps were established with the markers thatfollowed the Mendelian segregation ratio 1:1. Finally, usingthe framework maps as references, JoinMap was used to gen-erate maps for each parent using all markers. The indepen-dence test logarithm (base) of odds (LOD), a minimumLOD threshold of 3.0, was used to group markers usingJoinMap. Map distances in centiMorgans (cM) were calculat-ed using maximum likelihood algorithm and Haldane map-ping function. Linkage groups (LGs) were named with FORor MUR (representing ‘Fortune’ or ‘Murcott’), followed by anumber corresponding to one of the nine main Clementinescaffolds. Genetic maps with QTL positions were drawn bythe program MapChart 2.2 (Voorrips 2002).

QTL mapping

Due to non-normality of some fruit traits, the raw phenotypicand genotypic data were analyzed by the Kruskal-Wallis rank-

sum test using MapQTL 6.0 (Van Ooijen 2011a). JMPGenomics 6.0 was used to perform QTL analysis on the pa-rental maps separately for each trait. QTLs were detectedusing interval mapping (IM) initially and nearby loci withthe highest LOD scores were used as co-factors. Then, com-posite interval mapping (CIM) (Jansen and Stam 1994; Zeng1994) with the expectation maximization (EM) mapping al-gorithm (Lander and Botstein 1989) was performed to detectadditional QTLs that might be masked by the major QTLs.LOD thresholds were calculated with a 1000-permutation testfor each trait on each map (Churchill and Doerge 1994). AQTL test step of 2 cM was used for CIM. QTLs with LODscores higher than the LOD threshold were reported. QTLswere literally named using trait abbreviation followed by thenumber of the LG in which the QTL was located.

Candidate gene identification and QTL validation

The detected QTLs were compared to the map position of fruitquality-related genes annotated in the Citrus clementina path-way s f r om the C i t r u sCyc Pa t hway s Da t ab a s e(http://pathways.citrusgenomedb.org/, part of the CitrusGenome Database) to identify potential candidate genes viacollocation of SNPs on both genetic maps and the Clementinegenome. The search for candidate genes within a QTL wasperformed only in the Clementine reference genome regiondelimited by the confidence interval of the QTL, using themost proximal SNPs that were both on the Clementinegenome sequence (http://www.phytozome.net/clementine.php) and the genetic linkage maps. Whether a gene waschosen as a candidate was based on the predicted annotationof the gene from the CitrusCyc Pathways Database, whichwas further confirmed by BLAST of the gene sequence fromthe Clementine genome against the Arabidopsis InformationResource (https://www.arabidopsis.org/).

The 13 citrus selections used for QTL validation weregrouped into two genotypic groups according to allelic con-figurations for each marker nearest to the QTL, and then, theANOVA was applied to test for the difference of the corre-sponding fruit trait between the two genotypic groups.

Results

Phenotypic distribution and relation between traits

The fruit quality traits were analyzed for ‘Fortune’, ‘Murcott’,and their derived F1 progeny over four samplings (Januaryand February in 2012 and 2013) and shown in theSupplementary material 2; ‘Fortune’ exhibited larger valuesin SD, TA, FCA, and FCAB and smaller values in ST, FCL,FCB, JCL, JCB, and JCAB, compared to ‘Murcott’. Most ofthe fruit traits were analyzed in the F1 population with similar

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mean values and standard deviations over four samplings.However, certain phenotypic variations were found amongfour samplings within parents, such as FW, JP, SSC, andJCA. Because of the high heterozygosity of the two parents,transgressive individuals were expected and detected at a highpercentage for several traits, which ranged from 9.68 % forJCB in 2013 Jan. sampling to 100 % for FD in 2013 Feb.According to the kurtosis and skewness values, only JCL,JCA, JP, TA, FCA, and JCB at certain samplings exhibitedabsolute values of kurtosis and/or skewness larger than 2.0(Supplementary material 2). All the fruit traits showed contin-ual variation, although their distributions were generallyskewed and/or significantly deviated from normality(p = 0.05, Fig. 1, Supplementary materials 1 and 2).

Pairwise correlation coefficients were calculated for all thetraits over four samplings, and several color characteristicswere correlated with each other (Supplementary material 3).High correlations (|r| > 0.5) were observed over four sam-plings in several traits, including positive correlation betweenFCL and FCB, FCA and FCAB, and JCA and JCAB andnegative correlation between TA and ST, FCL and FCAB,and FCB and FCAB. Most correlation coefficients showedsimilar values over four samplings. In addition, there werealso observations of high correlation between some traits overthree samplings, including positive correlation between FWand FD, and JCL and JCB and negative correlation betweenFCL and FCA. Interesting high correlations were found be-tween traits in the two samplings in 2013; FD correlated neg-atively with SSC and TA, FW correlated negatively with TA,and SSC correlated positively with TA. However, neither JPnor SD showed correlation with any other fruit traits. Theeffects of genotype, sampling date, and their interaction weresignificant (P < 0.0001) for all traits (Supplementary material4).

Marker segregation and polymorphism

Of the 1536 SNPs, 761 SNPs were discarded, including 108SNPs with more than 20 missing calls, 521 SNPs being ho-mozygous in two parents and 132 SNPs with no segregationin F1 individuals. The large numbers of homozygous and un-usable SNPs in the two mandarin cultivars can be attributed tothe fact that these 1536 SNPs were selected exclusively frompolymorphic nucleotides (haplotypes) presented in sweet or-ange sequencing reads and intended initially for a sweet or-ange genome mapping project. Finally, 775 SNPs (50.46 % oftotal) were imported into mapping programs for segregationand linkage analysis. More heterozygous markers were foundin ‘Fortune’ than in ‘Murcott’. Of the 775markers, 372 (48%)were heterozygous only in ‘Fortune’, 274 (35.36 %) wereheterozygous only in ‘Murcott’, and 129 (16.64 %) were het-erozygous in both parents. According to the χ2 test, 10 out of372 (2.69 %) ‘Fortune’ markers and 95 out of 274 (34.67 %)

‘Murcott’ markers showed segregation distortion (goodness-of-fit ratio 1:1, α = 0.05); 26 out of 129 (20.16 %) markerscommon to ‘Fortune’ and ‘Murcott’ showed segregation dis-tortion (goodness-of-fit ratio 1:2:1, α = 0.05).

Genetic maps for ‘Fortune’ × ‘Murcott’

The <lmxll> and <nnxnp> type markers were selected to con-struct parental framework maps using JoinMap. Parentalframework maps were established and used as reference mapsto construct final parental maps using JoinMap with the ML(maximum likelihood) mapping algorithm. The linkages ofFOR and MUR map were strong ranging from LOD 3.0 to10.0. Most of the LGs kept their integrity up to LOD 7.0 orhigher. FOR1, MUR3, and MUR4 kept integrity up to LOD10.0, as did FOR8 up to LOD 9.0. LGs were split by relativelywide intervals without intermediate markers. Eventually, thegenetic maps representing all nine chromosomes were con-structed (Table 2, Supplementary material 5 and Fig. 2),FOR1 to FOR9 for the maternal map, and MUR1 to MUR9for the paternal map; the numbers corresponded to theClementine genome scaffolds. The FOR map consisted of189 SNPs, spanning 681.07 cM on nine LGs, with an averageinterval length of 4.08 cM. The size in cM varied among nineLGs from 20.1 of LG9 to 129.6 of LG3. The MUR mapconsisted of 106 SNPs, spanning 395.25 cM on nine LGs,with an average interval length of 4.34 cM. The size in cMvaried among nine LGs from 8.2 of LG2 to 92.06 of LG3.High linear correlation was observed between length of LGsand number of markers on it for the parental maps (r = 0.73,p = 0.0005).

Physical distribution of SNP-containing sequences

Synteny was highly conserved between the mandaringenetic map and the Clementine genome sequence(Table 2, Supplementary material 5). The non-syntenicmatch occurred mainly on FOR7, in which seven SNPsequences between 19.651 and 25.375 cM were alignedto 22,945,200 to 12,781,158 bp in scaffold 5 of theClementine genome; one SNP sequence each wasaligned to scaffolds 1, 6, and 10. Other minor syntenicdiscrepancies included one SNP sequence on FOR8.1that was aligned to scaffold 3, one and two SNPs onMUR8 were aligned to scaffolds 9 and 3, respectively,and one SNP on FOR2.2 was aligned to scaffold 55.The corresponding physical coverage of the parentalmaps on the Clementine genome sequence varied from13.49 % of scaffold 9 to 95.21 % of scaffold 6 for theFOR map and from 11.61 % of scaffold 2 to 93.58 %of scaffold 8 for the MUR map (Table 2).

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Identification of QTLs and candidate genes

A total of 68 significant associations were found betweenmarkers and fruit traits (Table 3). Because QTLs for eachphenotype located in the same chromosomal regions fromdifferent harvest seasons were considered to be the same, the68 associations then were summarized into 48 QTLs. Amongthem, ten were consistent over two or more samplings and areindicated in underlined font in Table 3. A total of 23 QTLs

were mapped to the FOR map and 25 to the MUR map. Thenumbers of QTLs per trait ranged from one for JP to six forFCAB. The average R2 (explained phenotypic variance) for alltraits was 24.46 % and ranged from 14.44 % for FCA8-2013Jto 49.44 % for FCA4.1-2012J with the highest LOD value of11.85. These QTLs and putatively relevant genes were de-scribed below in detail based on their LGs (Fig. 2).

Three non-repeatable QTLs were identified for FD, whileone non-repeatable and two repeatable QTLs were detected

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Fig. 1 Frequency distributions ofmandarin quality traits for the F1population in 2013 Januarysampling

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for FW. The QTL FD4.2was overlapped with FW4.2, with R2

being 20.5 and 24.6 %, respectively. FW5.1 and FD5.1 wereoverlapped on FOR. FW5.1 was stable over two samplingswith R2 being 24.55 and 15.03 %, while FD5.1 was onlyfound from one sampling. FW8 was stable over three sam-plings with R2 being 21.2, 20.59, and 14.98 %. Two and onenon-repeatable QTLs were identified for SD and JP, respec-tively. Five and three non-repeatable QTLs were identified forSSC and ST, respectively, while two non-repeatable and one

repeatable QTLs were detected for TA. TA7.1 and ST7.1 wereoverlapped with R2 being 19.8 and 20.52 %, respectively. TA8and SSC8 were overlapped with R2 being 24.77 and 15.72 %,respectively. ST9 and TA9 were overlapped, ST9 was onlyfound in one sampling, and TA9 was stable over two sam-plings with R2 being 20.03 and 19.33 %, respectively.

A total of 28 QTLs were identified for peel and juicecolor traits, and seven of them were repeatable. A clus-ter of QTLs on MUR4.1 were identified for FCL, FCA,

Table 2 Mapping data summary of the mandarin genetic maps in the ‘Fortune’ × ‘Murcott’ F1 population

LG Clementine syntenic scaffold Number ofmarkers

Genetic size(cM)

Mapped to syntenicClementine scaffold

Mapped to otherClementine scaffold

Genome coverage(%)

FOR MUR FOR MUR FOR MUR FOR MUR FOR MUR

1 1 24 7 81.21 40.11 24 6 0 1 67.3 70.45

2 2 17 5 65.32 8.2 16 5 1 0 58.74 11.61

3 3 37 17 129.6 92.06 37 17 0 0 65.89 86.86

4 4 22 9 36.44 33.87 22 9 0 0 66.2 25.46

5 5 26 7 65.64 37.53 26 7 0 0 46.05 63.59

6 6 13 7 110.66 30 13 7 0 0 95.21 65.09

7 7 34 6 102.07 25.61 24 5 10 1 88.38 43.14

8 8 9 26 70.03 58.8 8 23 1 3 93.46 93.58

9 9 7 22 20.1 69.07 7 22 0 0 13.49 91.98

Total 189 106 681.07 395.25 177 101 12 5

m277_s10.0

m279_s11.8

m677_s12.7

m409_s13.6

m282_s16.4

m209_s17.3

m690_s110.9

m908_s111.8

m363_s113.6

m87_s114.6

m187_s115.5

m1094_s122.8

m196_s123.7

m150_s124.6

m1393_s125.5

m1330_s128.2

m333_s133.7

m203_s136.5

m783_s142.9

m884_s144.7

m845_s149.2

m1210_s163.2

F3

10

2-

1.1

BC

FF

31

02

-1.

1A

CF

J3

10

2-

1.1

LC

FF

21

02

-1.

1B

AC

F

FOR1.1

m473_s10.0

m110_s118.0

FOR1.2

m1156_s20.0

m424_s24.6

m777_s29.1

m369_s210.0

m842_s211.9

m465_s212.8

m54_s213.7

m301_s220.1

m676_s222.8

m70_s224.6

m80_s5525.5

m794_s238.5

m1309_s250.6

m447_s261.7

F2

10

2-

2.2

BA

CF

F3

10

2-

2.2

CS

SF

21

02

-2.

2B

CJ

FOR2.2

m1492_s20.0

m423_s22.7

m141_s23.6

FOR2.1

m1362_s30.0

m357_s311.1

m590_s325.1

m1223_s326.0

J3

10

2-

1.3

DS

FOR3.1

m596_s30.0

m1523_s32.1

m1207_s39.1

m1347_s313.9

m353_s320.5

m464_s321.0

m924_s321.9

FOR3.2

m1455_s30.0

m156_s35.9

m92_s36.8

m1241_s37.8

m572_s39.6

m23_s312.5

m1209_s316.4

m405_s317.3

m238_s318.2

m17_s320.1

m66_s321.0

m261_s325.9

m837_s333.9

J2

10

2-

3.3

CS

S

F3

10

2-

3.3

BA

CF

F3

10

2-

3.3

BA

CJ

FOR3.3

m751_s30.0

m643_s33.6

m191_s34.5

m1417_s36.4

m1471_s37.3

m116_s39.1

m914_s310.0

m797_s332.3

m1081_s335.9

m985_s338.7

m31_s343.2

m564_s344.1

m838_s347.8

FOR3.4

m834_s40.0

m971_s40.9

m1348_s43.6

m285_s48.2

FOR4.1

m731_s40.0

m314_s40.9

m538_s41.8

m84_s47.3

m399_s49.1

m1002_s411.8

m71_s414.6

m988_s415.5

m38_s416.4

m1395_s418.2

m1119_s419.2

m361_s420.1

m1039_s421.9

m1277_s422.8

m220_s423.7

m192_s424.6

m347_s425.5

m1074_s428.2

F3

10

2-

2.4

CS

S

FOR4.2

m682_s50.0

m591_s54.6

m122_s56.4

m175_s59.1

m462_s512.8

m816_s514.6

m410_s517.3

m28_s523.7

m19_s524.6

m367_s525.5

m81_s527.3

m620_s533.7

m1297_s537.4

m1131_s538.3

m896_s540.1

m1072_s541.0

m1291_s544.7

m128_s545.6

m1115_s547.4

m559_s549.2

m219_s550.1

m1068_s555.6

m828_s557.4

m49_s559.2

F2

10

2-

1.5

WF

J3

10

2-

1.5

WF

F2

10

2-

1.5

DF

FOR5.1

m787_s50.0

m1439_s56.4

FOR5.2

Fig. 2 Parental linkage groups with QTLs associated with mandarinquality traits. QTLs are identified on the ‘Fortune’ (FOR) and ‘Murcott’(MUR) linkage groups (LGs). Black bars represent QTLs with 1-LOD

support intervals. QTLs are literally named using trait abbreviationfollowed by the number of the LG in which the QTL is located. Thedetails of QTLs are presented in Table 3

Tree Genetics & Genomes (2016) 12: 77 Page 7 of 16 77

FCAB, FCB, JCA, and JCAB over three or all foursamplings. Their average R2 was 33.61 %, ranging from17.95 % for FCB4.1-2013F to 49.43 % for FCA4.1-2012J. Within the 1-LOD confidence intervals of theseQTLs for color, 689 genes were found in the

corresponding genome area on scaffold 4 of theClementine genome. Two of these genes, pds1 andccd4, encoding phytoene desaturation 1 and carotenoidcleavage dioxygenase 4, were probably related to fruitcolor regulation based on their annotation from the

m1467_s70.0

m1456_s72.9

m586_s73.9

m975_s75.8

m1501_s76.7

m307_s77.7

m739_s78.9

m223_s712.8

m1472_s615.7

m9_s519.7

m58_s521.6

m1283_s522.6

m270_s523.5

m1293_s5 m32_s524.4

m131_s525.4

m606_s1026.3

m1142_s727.3

m123_s128.1

m627_s729.0

m1412_s730.0

m664_s730.9

m91_s737.4

m741_s740.6

m245_s741.6

m860_s744.3

m1178_s745.2

m266_s749.2

J2

10

2-

1.7

BC

JJ

21

02

-1.

7T

S

J2

10

2-

1.7

AT

FOR7.1

m471_s70.0

m1380_s720.4

m463_s747.3

m304_s748.2

m565_s751.0

m759_s752.9

F2

10

2-

2.7

BA

CF

F2

10

2-

2.7

BC

F

F2

10

2-

2.7

LC

F

FOR7.2

m236_s80.0

m681_s86.4

m571_s837.0

m244_s843.4

m954_s863.5

FOR8.1

m569_s80.0

m392_s80.9

m1110_s84.6

m562_s36.5 F2

10

2-

2.8

BC

J

FOR8.2

m993_s90.0

m1003_s99.2 J2

10

2-

1.9

DS

FOR9.1

m395_s90.0

m390_s92.7

FOR9.2

m491_s90.0

m825_s92.7

m27_s98.2

F2

10

2-

3.9

DF

FOR9.3

m859_s60.0

m242_s630.6

m654_s669.8

J3

10

2-

1.6

AT

FOR6.1

m376_s60.0

m1258_s61.8

m97_s66.4

m839_s68.2

m1377_s69.1

m485_s612.8

m939_s613.7

FOR6.2

m12_s60.0

m782_s624.5

m1453_s627.3

FOR6.3

Fig. 2 (continued)

m674_s10.0

m1271_s131.0

MUR1.1

m1436_s10.0

m1109_s15.5

m499_s16.4

m468_s17.3

m133_s29.2

F3

10

2-

2.1

AC

F

F2

10

2-

2.1

TS

MUR1.2

m852_s20.0

m1534_s21.8

m167_s25.5

m512_s27.3

m1069_s28.2

J2

10

2-

2L

CJ

MUR2

m667_s30.0

m948_s32.7

m1333_s38.2

m349_s310.0

m161_s313.7

m331_s314.6

MUR3.1

m727_s30.0

m880_s310.1

m132_s332.4

m387_s333.3

m747_s345.4

m561_s349.0

m159_s353.6

m557_s364.7

J3

10

2-

2.3

BC

FJ

21

02

-2.

3C

SS

MUR3.2

m181_s30.0

m497_s38.3

m51_s312.8

MUR3.3

m560_s40.0

m847_s425.7

J2

10

2-

2.4

AC

J

F3

10

2-

2.4

DF

F3

10

2-

2.4

WF

F2

10

2-

2.4

BA

CJ

MUR4.2

m30_s50.0

m251_s54.6

m375_s524.7

m1172_s525.6

m1013_s535.7

m82_s536.6

m241_s537.5

F2

10

2-

5B

CF

MUR5

m65_s40.0

m163_s40.9

m532_s41.8

m959_s44.6

m1019_s45.5

m749_s47.3

m358_s48.2

J2

10

2-

1 .4

AC

F

F2

10

2-

1.4

AC

F

J3

10

2-

1.4

AC

F

F3

10

2-

1.4

AC

F

F2

10

2-

1.4

BA

CF

J3

10

2-

1.4

BA

CF

F3

10

2-

1.4

BA

CF

J2

10

2-

1.4

BC

F

F2

10

2-

1.4

BC

F

J3

10

2-

1.4

BC

F

F3

10

2-

1.4

BC

F

J2

10

2-

1.4

LC

F

F2

10

2-

1.4

LC

F

J3

10

2-

1.4

LC

F

F3

10

2-

1.4

LC

F

F2

10

2-

1.4

AC

J

J3

10

2-

1.4

AC

J

F3

10

2-

1.4

AC

J

J2

10

2-

1.4

BA

CJ

J3

10

2-

1.4

BA

CJ

F3

10

2-

1.4

BA

CJ

MUR4.1

Fig. 2 (continued)

77 Page 8 of 16 Tree Genetics & Genomes (2016) 12: 77

CitrusCyc Pathways database and biological function asstudied in model plant species such as Arabidopsis(Table 4). On MUR4.2, JCAB4.2 and JCA4.2 were o-verlapped with R2 being 29.3 and 19.34 %, respectively.FCL1.1 and FCB1.1 were overlapped on the FOR1.1map with R2 being 21.48 and 18.22 %, respectively,while FCAB1.1 and FCA1.1 were also overlapped onFOR1.1 with R2 being 21.02 and 18.26 %, respectively.FCL7.2, FCB7.2, and FCAB7.2 were overlapped onFOR7.2 with R2 being 25.3, 23.95, and 22.39 %, re-spectively. FCAB8 and FCA8 were overlapped onMUR8.2, FCAB8 was only found in one sampling,and FCA8 was stable over two samplings with R2 being19.35 and 14.44 %, respectively.

Validation of QTLs in citrus selections

All 48 QTLs were validated in 13 other citrus selectionsin the 2014 harvest season, with four of them showingthe potential for MAS in citrus breeding programs(Supplementary material 6). The 13 citrus selectionswere grouped into two genotypic classes, homozygousAA (or BB) and heterozygous AB, according to theallelic configurations for each SNP. A total of 10SNPs showed significant differences (p = 0.05) for theircorresponding traits between the two genotypic classes.For instance, m540_s8, the nearest SNP to FW8,showed significant differences for FW between the twoclasses.

Discussion

Mandarin fruit are non-climacteric, and maturity is pri-marily indicated externally by decreasing green colora-tion through degradation of chlorophyll and increasingorange appearance through carotenoid biosynthesis.Once color is fully developed, most fruit quality char-acteristics, such as peel color, flesh color, sugar content,and acid level, remain relatively stable for weeks, withusually only slight increases in color and sugars anddecreases in acidity. Although coloration is a very reli-able indicator for the maturity and harvest for citrusfruits, considering the inherent wide variations in thepopulation, we deliberately used two harvest timings tocapture the maximum likelihood of natural maturity andto ensure the reliability and reproducibility in measuringfruit quality characteristics. At each harvest, a total of15 fruits were sampled from each individual tree anddivided into three groups as biological replicates, inorder to capture the variance within individual trees;the same way was also found in the genetic mappingstudy of apple, peach, and apricot (Zhao et al. 2016;Eduardo et al. 2011; Socquet-Juglard et al. 2013).

Possible relation and interaction among fruit quality traits

Larger fruit size and less fruitlet abscission were correlatedwith the presence of seeds in fruits, and common markerswere associated with both increased fruit size and increasedseed number in a population of Citrus volkameriana ×

m1426_s60.0

m796_s61.8

m858_s625.2

m553_s626.1

MUR6.1

m514_s70.0

m292_s78.3

MUR7.1

m317_s70.0

m188_s75.5

F2

10

2-

2.7

BC

J

F2

10

2-

2.7

PJ

MUR7.2

m998_s90.0

m1462_s95.8

m717_s911.1

m1397_s919.9

m1183_s929.6

m467_s938.9

m288_s939.4

m21_s939.7

m388_s940.7

m25_s9 m925_s9

m93_s941.6

m1031_s942.5

m2_s942.6

m436_s943.0

m96_s943.7

m402_s944.6

m22_s945.5

m1228_s946.4

m262_s949.2

m983_s962.0

m1314_s969.1

F2

10

2-

9A

T

J2

10

2-

9A

T

J2

10

2-

9T

S

MUR9

m16_s60.0

m41_s60.9

m286_s63.9

MUR6.2

m180_s80.0

m57_s81.8

m1163_s814.8

m540_s816.6

m222_s829.6

m258_s832.4

m1536_s834.2

m55_s335.1

m1051_s336.0

m533_s936.9

m905_s837.8

m3_s838.8

m1022_s839.7

m1433_s840.6

m184_s841.5

m851_s842.4

m1336_s843.3

m53_s845.2

m524_s846.1

m318_s847.9

m18_s849.7

m1_s851.6

m757_s852.5

m48_s855.2

m1170_s856.1

m1300_s858.8

J3

10

2-

8C

SS

J3

10

2-

8W

FJ

31

02

-8

AC

F

F3

10

2-

8A

TF

21

02

-8

WF

J2

10

2-

8B

AC

F

J2

10

2-

8W

FF

21

02

-8

AC

F

MUR8

Fig. 2 (continued)

Tree Genetics & Genomes (2016) 12: 77 Page 9 of 16 77

Table 3 QTLs detected for fruit quality traits in the ‘Fortune’ × ‘Murcott’ F1 population

Trait QTLa Year Month LGb K-Wc LODthrd

LODmaxe

Positionf Nearestmarker

Markerpositiong

Effect R2

(%)h

Fruit diameter FD4.2 2013 Feb MUR4.2 *** 2.69 3.74 25.68 m847_s4 25.68 −16.61 20.50

r FD5.1 2012 Feb FOR5.1 ** 2.9 5.07 31.34 m620_s5 33.74 −18.21 29.42

FD9.3 2012 Feb FOR9.3 ** 2.9 3.00 4.7 m825_s9 2.7 9.17 18.61

Fruit weight FW4.2 2013 Feb MUR4.2 **** 2.7 4.60 25.68 m847_s4 25.68 −130.63 24.60

FW5.1 2012 Feb FOR5.1 ** 2.85 4.10 27.34 m81_s5 27.34 −130.34 24.55

2013 Jan FOR5.1 **** 2.81 3.11 29.34 m81_s5 27.34 −87.14 15.03

FW8 2012 Jan MUR8 ***** 2.91 3.20 31.6 m258_s8 32.4 62.30 20.59

2012 Feb MUR8 **** 2.76 3.47 29.6 m222_s8 29.6 67.75 21.20

2013 Jan MUR8 * 2.68 3.06 16.6 m540_s8 16.6 73.72 14.97

Juice percentage JP7.2 2012 Feb MUR7.2 ***** 2.78 4.05 0 m317_s7 0 12.21 24.60

Seed number SD3.1 2013 Jan FOR3.1 ** 2.94 4.58 11.09 m357_s3 11.09 5.03 21.32

SD9.1 2012 Jan FOR9.1 *** 2.89 3.12 9.2 m1003_s9 9.2 −2.63 19.59

Soluble solids content SSC2.2 2013 Feb FOR2.2 *** 2.92 3.19 35.53 m794_s2 38.54 −2.08 17.80

SSC3.2 2012 Jan MUR3.2 **** 2.56 3.45 28.14 m132_s3 32.41 2.15 18.42

SSC3.3 2012 Jan FOR3.3 *** 2.89 3.22 0 m1455_s3 0 2.09 17.32

SSC4.2 2013 Feb FOR4.2 **** 2.92 4.17 18.24 m1395_s4 18.24 −2.39 22.60

SSC8 2013 Jan MUR8 ** 2.73 3.23 0 m180_s8 0 2.86 15.72

Titratable acidity TA7.1 2012 Jan FOR7.1 **** 2.8 3.74 45.25 m1178_s7 45.25 −0.36 19.80

TA8 2013 Feb MUR8 ** 2.99 4.57 0 m180_s8 0 1.17 24.77

TA9 2012 Jan MUR9 ******* 2.77 3.78 40.65 m388_s9 40.65 −0.38 20.03

2012 Feb MUR9 ***** 2.79 2.94 39.72 m21_s9 39.72 −0.28 19.33

Soluble solids content/titratable acidity

ST1.2 2012 Feb MUR1.2 *** 2.73 3.99 2 m1436_s1 0 −3.79 25.30

ST7.1 2012 Jan FOR7.1 ***** 2.85 3.89 45.25 m1178_s7 45.25 4.17 20.52

ST9 2012 Jan MUR9 ******* 2.82 3.29 40.65 m388_s9 40.65 3.65 17.65

Flavedo color space value L FCL1.1 2013 Jan FOR1.1 ** 3.00 4.62 6.4 m282_s1 6.4 −4.95 21.47

FCL4.1 2012 Jan MUR4.1 ******* 2.58 8.97 1.82 m532_s4 1.82 5.07 40.33

2012 Feb MUR4.1 ******* 2.63 5.56 0.91 m163_s4 0.91 3.70 32.55

2013 Jan MUR4.1 ******* 2.66 9.83 0.91 m163_s4 0.91 5.27 40.55

2013 Feb MUR4.1 ******* 2.68 4.28 1.82 m532_s4 1.82 3.62 23.10

FCL7.2 2012 Feb FOR7.2 **** 3.09 4.12 0 m471_s7 0 −3.97 25.30

Flavedo color space value a FCA1.1 2013 Feb FOR1.1 ** 2.99 3.33 38.5 m203_s1 36.5 −6.64 18.26

FCA1.2 2013 Feb MUR1.2 ** 2.85 4.05 0 m1436_s1 0 −6.56 22.03

FCA4.1 2012 Jan MUR4.1 ******* 2.66 11.85 8.19 m358_s4 8.19 −9.21 49.43

2012 Feb MUR4.1 ******* 2.69 6.40 8.19 m358_s4 8.19 −6.61 36.43

2013 Jan MUR4.1 ******* 2.61 9.12 0.91 m163_s4 0.91 −8.10 38.31

2013 Feb MUR4.1 ******* 2.85 7.28 0.91 m163_s4 0.91 −7.86 36.05

FCA8 2012 Feb MUR8 * 2.69 3.04 58.8 m1300_s8 58.8 −6.91 19.35

2013 Jan MUR8 ****** 2.61 2.95 43.3 m1336_s8 43.3 −3.98 14.44

Flavedo color space value b FCB1.1 2013 Feb FOR1.1 **** 2.87 3.32 0 m277_s1 0 −3.16 18.22

FCB3.2 2013 Jan MUR3.2 *** 2.71 3.58 0 m727_s3 0 2.14 17.24

FCB4.1 2012 Jan MUR4.1 ******* 2.5 6.37 7.28 m749_s4 7.28 2.85 30.70

2012 Feb MUR4.1 ******* 2.6 6.31 0.91 m163_s4 0.91 2.67 36.06

2013 Jan MUR4.1 ******* 2.71 9.75 1.82 m532_s4 1.82 3.69 40.31

2013 Feb MUR4.1 ******* 2.53 3.22 0.91 m163_s4 0.91 2.38 17.95

FCB5 2012 Feb MUR5 ** 2.6 3.40 25.58 m1172_s5 25.58 −2.09 21.40

FCB7.2 2012 Feb FOR7.2 **** 3.00 3.86 0 m471_s7 0 −2.88 23.95

Flavedo color space value a/b

FCAB1.1 2012 Feb FOR1.1 *** 3.05 3.33 42.9 m783_s1 42.9 −0.22 21.02

FCAB2.2 2012 Feb FOR2.2 ** 3.05 3.77 13.67 m54_s2 13.67 0.20 23.43

77 Page 10 of 16 Tree Genetics & Genomes (2016) 12: 77

P. trifoliata (García et al. 2000). The association between fruitsize and seed number in the population can be a genetic ob-stacle for mandarin breeders to target both large size andseedlessness, at least in hybrid families that lack parthenocar-pic potential. There was no high correlation between SD andFD or FW in the ‘Fortune’ × ‘Murcott’ hybrids. The QTLs for

FWand FD overlapped on LG FOR5.1 and MUR4.2, respec-tively, which confirmed the high correlation between FD andFW and is in agreement with the common genome regioncontrolling both fruit weight and size in a population ofC. volkameriana × P. trifoliata (García et al. 2000). It has beenobserved in tomato that fruit size and weight are negatively

Table 3 (continued)

Trait QTLa Year Month LGb K-Wc LODthrd

LODmaxe

Positionf Nearestmarker

Markerpositiong

Effect R2

(%)h

FCAB3.3 2013 Feb FOR3.3 ****** 2.92 3.42 9.65 m572_s3 9.65 −0.24 18.72

FCAB4.1 2012 Feb MUR4.1 ******* 2.68 7.75 8.19 m358_s4 8.19 −0.28 42.26

2013 Jan MUR4.1 ******* 2.64 11.32 5.46 m1019_s4 5.46 −0.36 45.08

2013 Feb MUR4.1 ******* 2.71 7.69 0.91 m163_s4 0.91 −0.33 37.64

FCAB7.2 2012 Feb FOR7.2 **** 3.05 3.58 4 m471_s7 0 0.21 22.39

FCAB8 2012 Jan MUR8 ** 2.63 2.85 58.1 m1300_s8 58.8 −0.15 15.13

Juice color space value L JCL2 2012 Jan MUR2 ** 2.5 3.10 7.28 m512_s2 7.28 −0.55 16.74

Juice color space value a JCA4.1 2012 Feb MUR4.1 ******* 2.61 5.80 8.19 m358_s4 8.19 −0.27 34.14

2013 Jan MUR4.1 ******* 2.69 5.05 1.82 m532_s4 1.82 −0.15 23.46

2013 Feb MUR4.1 ******* 2.58 5.83 7.28 m749_s4 7.28 −0.17 30.41

JCA4.2 2012 Jan MUR4.2 ****** 2.69 3.64 25.68 m847_s4 25.68 0.17 19.34

Juice color space value b JCB2.2 2012 Feb FOR2.2 ** 2.86 3.66 60.59 m447_s2 61.68 −0.21 23.16

JCB7.1 2012 Jan FOR7.1 ** 2.65 4.25 29.95 m1412_s7 29.95 0.55 22.18

JCB7.2 2012 Feb MUR7.2 *** 2.77 3.01 0 m317_s7 0 0.43 19.46

JCB8.2 2012 Feb FOR8.2 ** 2.86 3.31 2.911 m1110_s8 4.604 −0.21 21.21

Juice color space value a/b JCAB3.3 2013 Feb FOR3.3 ** 2.97 3.36 17.29 m405_s3 17.29 0.17 18.66

JCAB4.1 2012 Jan MUR4.1 ******* 2.65 3.74 0 m65_s4 0 −0.10 19.81

2013 Jan MUR4.1 ******* 2.74 4.53 0.91 m163_s4 0.91 −0.08 21.33

2013 Feb MUR4.1 ******* 2.58 5.71 7.28 m749_s4 7.28 −0.11 29.92

JCAB4.2 2012 Feb MUR4.2 ******* 2.62 4.82 25.68 m847_s4 25.68 0.47 29.30

p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; *****p < 0.00001; ******p < 0.000001; *******p < 0.0000001aQTLs are literally named using trait abbreviation followed by the number of the LG in which the QTL is located. Those QTLs identified in two or morethan two harvest seasons are indicated in underlined fontb Linkage groupc Significance level of Kruskal-Wallis testd LOD threshold determined by 1000 permutation tests for each trait in each sampling and each mape The LOD maximum for each QTLf The QTL position (in cM) from the top of LGg The nearest marker position (in cM) from the top of LGh The percentage of the total phenotypic variation explained by the QTL

Table 4 Genes in linkage group 4 that may participate in mandarin fruit color regulation

Gene ID Position Gene symbol Description TAIRa hit name References

Ciclev10031003m 18,266,262–18,268,327 CCD4,NCED4

Nine-cis-epoxycarotenoid dioxygenase4

AT4G19170.1 Gonzalez-Jorge et al.(2013))

Ciclev10031587m 15,473,804–15,476,351 HPD, PDS1 Phytoene desaturation 1 AT1G06570.1 Norris et al. (1998))

a The Arabidopsis Information Resource

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correlated with SSC and TA (Georgelis et al. 2004), and thepresent study in mandarin is in agreement with that observa-tion. A positive correlation between SSC and TAwas found intwo samplings, but no QTL interval was shared by these traits.

The effect of genotype × environment interaction played animportant role on citrus fruit quality traits, which was con-firmed by the significant effect of genotype × sampling datefor all mandarin fruit quality traits. The exterior characteris-tics, such as FD and FW, fluctuated more markedly than inte-rior fruit traits, such as SD, JP, and juice colors. The fruits onboth the ‘Murcott’ tree and hybrids were observed to be heavi-er in 2012 than in 2013 in this study. According to previousreports, citrus FW differences among years were largely dueto the amount of rain (García et al. 2000), but fruit sizes canalso be influenced by crop load (Wheaton 1997). In the man-darin hybrids here, seven correlations between fruit traits wereconsistent over all samplings, but another 13 correlations werenot. In our case, the hybrids in the population used for traitevaluation were not exactly the same over samplings, withsome hybrids excluded from year to year because no fruitwere found on these trees; alternate bearing can be a commonphenomenon in mandarins. Variations in relative crop loadspartly due to biennial bearing likely caused the differences insome fruit traits of the ‘Fortune’ × ‘Murcott’ progeny amongsamplings.

Transgression is often observed in the progeny derivedfrom interspecific mating. Transgressive segregation resultsfrom new combinations in progeny plants of multiple geneswith more positive or more negative effects on a quantitativetrait than were present in either parent (Sleper and Poehlman2006). The ‘Fortune’ × ‘Murcott’ progeny showed highlytransgressive segregation with respect to every fruit qualitycharacteristic here. The wide variation in each fruit traitamong the mandarin hybrids could be used to generate recom-bination with markedly improved mandarin fruit quality.Multiple QTLs were identified for all traits except JP andJCL, in agreement with the highly transgressive segregationand polygenic inheritance for each fruit trait in the progenyplants. In our study, the QTL interval on LG4 for FCA,FCAB, FCB, JCA, and JCABwas consistent through all sam-plings, while the other QTLs were not, revealing important G× E interaction effects. The G × E interaction at the molecularlevel probably affected the stability in the expression of themajority of the detected QTLs across samplings (García et al.2000).

Consistent correlation was found between color space val-ue L with a and b in flavedo, while L only correlated with b injuice. The subsequent QTL analysis confirmed this result;overlapping of QTLs for JCL and JCA was not observed.The high correlation between L and b both in fruit peel andflesh was reported in sweet cherry (Sooriyapathirana et al.2010), which revealed a common genetic mechanism control-ling the two color characteristics.

Map synteny between the linkages and genome scaffolds

A ‘Fortune’ mandarin genetic map was built from a popula-tion of a reciprocal cross ‘Fortune’ × ‘Chandler’ pummelospanning 577 cM on 13 LGs with 95 markers (mostly SSRand IRAP (inter retro-transposon amplified polymorphism)),but the mapped markers were insufficient to establish nineLGs corresponding to nine chromosomes (Bernet et al.2010). The ‘Fortune’ genetic map built here spanned681.07 cM, longer than the previous one, on nine LGs withsome of them being broken to two or three subgroups. A‘Murcott’ mandarin genetic map was constructed usingAFLP markers from a population of ‘Murcott’ × ‘Pera’ or-ange, with 227 markers on 209 marker sites on nine LGs of845 cM; the average distance amongmarkers was 4.25 cM (deOliveira et al. 2007; Bastianel et al. 2009). Compared to theprevious one, here, the ‘Murcott’ map had the similar markerdensity, 4.34 cM, but the map length was 53.22 % shorter.This was due to insufficient SNP markers on some LGs, suchas MUR2 and MUR7. Differences among the lengths of LGsin the current parental maps were observed and similar to theprevious Clementine reference map (Ollitrault et al. 2012a). Inthe mandarin parental maps here, LG3 was the longest one,while FOR6 andMUR9were the shorter LG on FORmap andMUR map, respectively.

Highly conserved synteny was observed between thegenetic maps and the Clementine genome sequence. Thisis in agreement with high marker colinearity conserva-tion existing among Citrus (mandarin, pummelo, sweetorange, sour orange, and Clementine) and between Citrusand Poncirus (Chen et al. 2008; Bernet et al. 2010;Ollitrault et al. 2012a). In the current study, a fragmentof LG7 corresponded to a 10 Mbp genome region on theClementine genome scaffold 5. In addition, small markerorder inversions and translocations existed almost withinevery LG in the mandarin map here. Although chromo-somal rearrangements were reported on C. reticulata ×C. maxima (Bernet et al. 2010), C. sinensis × P. trifoliata(Chen et al. 2008), and C. clementina × C. maxima(Ollitrault et al. 2012a), the relatively small populationand missing genotyping data for some individuals in thisstudy might also contribute to some marker positiondiscrepancies.

Distorted segregation of molecular markers has been ob-served frequently in genetic mapping studies of Citrus (deOliveira et al. 2007; Bernet et al. 2010; Ollitrault et al.2012a; Raga et al. 2012). In the present study, 34.7 % of malemarkers (heterozygous in ‘Murcott’) showed segregation dis-tortion, which was much higher than that of female markers(2.7 %). The same difference was found in the Clementinelinkage map with skewed markers accounting for 57 % ofmale and 13 % of female markers (Ollitrault et al. 2012a).Bernet et al. also observed a higher percentage of distorted

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segregation in male than that in female in a reciprocal cross of‘Chandler’ pummelo × ‘Fortune’ mandarin (Bernet et al.2010). Gametic selection was believed to be the causing factorof higher distorted segregation in male compared to femaleparent (Ollitrault et al. 2012a).

Candidate genes found in some QTLs

Acid, sugar, and color are among the most important attributesrelevant to the flavor and acceptance of citrus fruit. In ripecitrus fruit, citric acid accounts for approximately 90 % ofthe total organic acid content, and the major sugars are fruc-tose, glucose, and sucrose (Sinclair 1984). Variation in thetotal organic acid content, the ratios of organic acids, the totalsugar content, and the ratios of monosaccharides was ob-served among citrus cultivars (Albertini et al. 2006). The sin-gle recessive gene, acitric, controlled the acidless trait inPummelo 2240 (also named ‘Siamese sweet’) (Fang et al.1997). In our study, five QTLs were detected for SSC andthree for TA; of these, one for TA was stable over two sam-plings. Most of the SSC and TA QTLs were minor contribu-tors, and R2s of 24.77 and 22.6%were the two larger ones. Nocandidate gene was identified in corresponding genomic re-gions of these QTL intervals.

Carotenoids are the major chemical components that deter-mine mandarin fruit colors and greatly vary among Citrusvarieties. Mature mandarin fruit predominantly accumulateβ-cryptoxanthin in flavedo and flesh (Goodner et al. 2001;Ikoma et al. 2001; Matsumoto et al. 2007), while sweet orangefruits predominantly accumulate nine-cis-violaxanthin and alltrans-violaxanthin (Matsumoto et al. 2007; Lee and Castle2001; Wei et al. 2014). In citrus fruits, the development ofpeel color from green to orange is linked to decreased expres-sion of ε-lycopene cyclase and increased expression of β-lycopene cyclase and a change from production of α-carotene and lutein to production of β-carotene, β-cryptoxanthin, zeaxanthin, and violaxanthin (Kato et al.2004). Massive accumulation of lycopene was reported tocontribute to the red flesh in citrus mutants (Liu et al. 2007;Xu et al. 2006; Lee 2001).

In the present study, a total of 28 QTLs were identified forflavedo and juice color characteristics; of these, sevenQTLsweredetected over multiple samplings. A QTL interval on LG4 iden-tified for FCL, FCA, FCAB, FCB, JCA, and JCAB throughthree or all four samplings contains pds1 and ccd4, encodingphytoene desaturation 1/hydroxyphenylpyruvate dioxygenase(PDS1/HPPDase) and carotenoid cleavage dioxygenase 4(CCD4), respectively. HPPDase is involved in plastoquinonepathway via catalysis of hydroxyphenylpyruvate (HPP) to formhomogentisate (HGA) (Garcia et al. 1997). HGA and solanesyldiphosphate (SDP) are used as substrates to produceplastoquinone-9 (PQ-9) after condensation, methylation, and ox-idation. Plastoquinone plays a critical role in carotenoid

biosynthetic as an electron carrier (Norris et al. 1995). TheArabidopsis pds1 mutant was unable to desaturate phytoene,accumulated phytoene, and was deficient both in plastoquinoneand tocopherol (Norris et al. 1995; Norris et al. 1998). Phytoenedesaturation is the first reaction in the carotenoid biosyntheticpathway to convert the colorless compound to colored pigmentsin plants and is considered to be a rate-limiting step in the path-way (Chamovitz et al. 1993). Carotenoids can be cleaved at anyconjugated double bonds by the CCD family to yield a widerange of apocarotenoids, which serve in plants as antifungalagents, as well as contributors to aroma of flowers and fruits(Auldridge et al. 2006b). The molecular mapping studies ofArabidopsis identified ccd4 as a large-effect QTL, negativelyregulating seed carotenoid content, especially β-carotene, andplaying a dominant role in β-carotene degradation in dry seedsand leaves (Gonzalez-Jorge et al. 2013). Compared toArabidopsis ccd4 mutant, ccd1 mutant also significantly in-creased seed lutein, neoxanthin, violaxanthin, and β-carotenerelative to the wild type, with a less or equal effect (Gonzalez-Jorge et al. 2013; Auldridge et al. 2006a). CCD4 contributed towhite color formation in potato flesh and chrysanthemum petalsby cleaving carotenoids into colorless compounds (Ohmiya et al.2006; Campbell et al. 2010). The ccd4 expression level washighly associated with carotenoid accumulation and responsiblefor flesh color in peach fruit (Brandi et al. 2011; Falchi et al.2013).

Implication for fruit quality MAS in citrus breeding

All the 48 QTLs were validated in 13 citrus selections in the2014 harvest season, and the results could open the opportu-nities for fruit quality MAS in citrus breeding. Selection of theappropriate allelic configurations of molecular markers mayassist identification of superior mandarin seedlings. For in-stance, the QTL FCAB8 linked marker m1336_s8 could beused to screen individuals for external color traits, as individ-uals with allelic configuration BB usually exhibited more or-ange color relative to individuals with allelic configurationAB. However, the QTLs identified in bi-parental crossesshould be validated in broad breeding germplasm and othersegregating populations grown in multiple years and loca-tions, in order to test the significance of QTL × environmentinteractions as well as QTL epistasis effects. Therefore, thehigh associations between some SNP defining QTL and fruitquality characteristics are promising but require future valida-tion under multiple environments.

Conclusions

SNP-based genetic maps were generated for two mandarincultivars (‘Fortune’ and ‘Murcott’) using the IlluminaGoldenGate assay. A total of 48 QTLs were identified for fruit

Tree Genetics & Genomes (2016) 12: 77 Page 13 of 16 77

traits, including fruit size and weight, juice percentage, seednumber, flavedo and juice colors, sugar, and acids. SeveralSNPs associated with the fruit characteristics showed the po-tential of MAS, although further validation in more materialsmay be needed.

Acknowledgments This work was partly funded by New VarietiesDevelopment & Management Corporation, Citrus Research andDevelopment Foundation, and the University of Florida PlantMolecular Breeding Initiative. The authors thank Yanzi Zhang,Marjorie Wendell, Xu Wei, Qibin Yu, and Misty Holt for technical assis-tance, as well as Sanghamitra Das for help with editing and HarryKlee forcritical reading of the manuscript.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conflicts ofinterest.

Author’s contributions FGG and CC conceived and designed thestudy; the mapping population was developed within the breeding pro-gram of FGG. YY carried out the work, analyzed the data, and wrote themanuscript. CC developed the GoldenGate array and read SNP genotyp-ing data. CC and FGG critically read and revised the manuscript. Allauthors read and approved the final manuscript.

Data archiving statement The SNPs, genetic maps, and QTL datareported in this manuscript will be made publicly available through theCitrus Genome Database (www.citrusgenomedb.org).

References

Albertini M-V, Carcouet E, Pailly O, Gambotti C, Luro F, Berti L (2006)Changes in organic acids and sugars during early stages of develop-ment of acidic and acidless citrus fruit. J Agric Food Chem 54(21):8335–8339. doi:10.1021/jf061648j

Aldrich J, Cullis CA (1993) RAPD analysis in flax: optimization of yieldand reproducibility using Klen Taq 1 DNA polymerase, Chelex 100,and gel purification of genomic DNA. Plant Mol Biol Report 11(2):128–141. doi:10.1007/bf02670471

Aleza P, Cuenca J, Juarez J, Pina JA, Navarro L (2010) ‘Garbi’mandarin:a new late-maturing triploid hybrid. Hortscience 45(1):139–141

Auldridge ME, Block A, Vogel JT, Dabney-Smith C, Mila I, BouzayenM, Magallanes-Lundback M, DellaPenna D, McCarty DR, Klee HJ(2006a) Characterization of three members of the Arabidopsis ca-rotenoid cleavage dioxygenase family demonstrates the divergentroles of this multifunctional enzyme family. Plant J 45(6):982–993. doi:10.1111/j.1365-313X.2006.02666.x

Auldridge ME, McCarty DR, Klee HJ (2006b) Plant carotenoid cleavageoxygenases and their apocarotenoid products. Curr Opin Plant Biol9(3):315–321. doi:10.1016/j.pbi.2006.03.005

Baldwin KL, Jones KG (2013) U.S. Citrus import demand: seasonalityand substitution. J Int Food Agric Mark 25(1):24–41. doi:10.1080/08974438.2013.724003

Barry G, Gmitter F, Chen C, Roose M, Federici C (2014) Investigatingthe parentage of ‘Orri’ and ‘Fortune’mandarin hybrids. Acta Hortic1065:449–456

Bastianel M, Cristofani-Yaly M, de Oliveira AC, Freitas-Astua J, FrancoGarcia AA, Vilela de Resende MD, Rodrigues V, Machado MA(2009) Quantitative trait loci analysis of citrus leprosis resistance

in an interspecific backcross family of (Citrus reticulata Blanco xC. sinensis L. Osbeck) x C. sinensis L. Osb. Euphytica 169(1):101–111. doi:10.1007/s10681-009-9950-3

Bernet GP, Fernandez-Ribacoba J, Carbonell EA, Asins MJ (2010)Comparative genome-wide segregation analysis and map construc-tion using a reciprocal cross design to facilitate citrus germplasmutilization. Mol Breed 25(4):659–673. doi:10.1007/s11032-009-9363-y

Brandi F, Bar E, Mourgues F, Horvath G, Turcsi E, Giuliano G, LiveraniA, Tartarini S, Lewinsohn E, Rosati C (2011) Study of ‘Redhaven’peach and its white-fleshed mutant suggests a key role of CCD4carotenoid dioxygenase in carotenoid and norisoprenoid volatilemetabolism. BMC Plant Biol 11:24–24. doi:10.1186/1471-2229-11-24

Cai Q, Guy CL, Moore GA (1994) Extension of the linkage map in citrususing random amplified polymorphic DNA (RAPD) markers andRFLP mapping of cold-acclimation-responsive loci. Theor ApplGenet 89(5):606–614

Campbell R, Ducreux LJM,MorrisWL,Morris JA, Suttle JC, Ramsay G,Bryan GJ, Hedley PE, Taylor MA (2010) The metabolic and devel-opmental roles of carotenoid cleavage dioxygenase4 from potato.Plant Physiol 154(2):656–664. doi:10.1104/pp.110.158733

Chamovitz D, Sandmann G, Hirschberg J (1993) Molecular andbiochemical-characterization of herbicide-resistant mutants ofcyanobacteria reveals that phytoene desaturation is a rate-limitingstep in carotenoid biosynthesis. J Biol Chem 268(23):17348–17353

Chen C, Gmitter FG (2013) Mining of haplotype-based expressed se-quence tag single nucleotide polymorphisms in citrus. BMCGenomics 14(1):746

Chen C, Bowman KD, Choi YA, Dang PM, Rao MN, Huang S, SonejiJR, McCollum TG, FG G Jr (2008) EST-SSR genetic maps forCitrus sinensis and Poncirus trifoliata. Tree Genet Genomes 4(1):1–10. doi:10.1007/s11295-007-0083-3

Churchill GA, Doerge RW (1994) Empirical threshold values for quanti-tative trait mapping. Genetics 138(3):963–971

Cristofani M,MachadoMA, Grattapaglia D (1999) Genetic linkage mapsof citrus sunki Hort. ex. Tan. and Poncirus trifoliata (L.) Raf. andmapping of citrus tristeza virus resistance gene. Euphytica 109(1):25–32. doi:10.1023/a:1003637116745

Dalkilic Z, Timmer LW, Gmitter FG (2005) Linkage of an Alternariadisease resistance gene in mandarin hybrids with RAPD fragments.J Am Soc Hortic Sci 130(2):191–195

Durham RE, Liou PC, Gmitter FG, Moore GA (1992) Linkage of restric-tion fragment length polymorphisms and isozymes in citrus. TheorAppl Genet 84(1–2):39–48

Eduardo I, Pacheco I, Chietera G, Bassi D, Pozzi C, Vecchietti A, RossiniL (2011) QTL analysis of fruit quality traits in two peach intraspe-cific populations and importance of maturity date pleiotropic effect.Tree Genet Genomes 7(2):323–335. doi:10.1007/s11295-010-0334-6

Falchi R, Vendramin E, Zanon L, Scalabrin S, Cipriani G, Verde I,Vizzotto G, Morgante M (2013) Three distinct mutational mecha-nisms acting on a single gene underpin the origin of yellow flesh inpeach. Plant J 76(2):175–187. doi:10.1111/tpj.12283

Fanciullino A-L, Cercos M, Dhuique-Mayer C, Froelicher Y, Talon M,Ollitrault P, Morillon R (2008) Changes in carotenoid content andbiosynthetic gene expression in juice sacs of four orange varieties(Citrus sinensis) differing in flesh fruit color. J Agric Food Chem56(10):3628–3638. doi:10.1021/jf0732051

Fang DQ, Federici CT, Roose ML (1997) Development of molecularmarkers linked to a gene controlling fruit acidity in citrus. Genome40(6):841–849

Furr JR (1964) New tangerines for the desert. Calif Citrograph 49:266–276Garcia I, Rodgers M, Lenne C, Rolland A, Sailland A, Matringe M

(1997) Subcellular localization and purification of a p-hydroxyphenylpyruvate dioxygenase from cultured carrot cells and

77 Page 14 of 16 Tree Genetics & Genomes (2016) 12: 77

characterization of the corresponding cDNA. Biochem J 325:761–769

García MR, Asins MJ, Carbonell EA (2000) QTL analysis of yield andseed number in citrus. Theor Appl Genet 101(3):487–493

Garcia R, Asins MJ, Forner J, Carbonell EA (1999) Genetic analysis ofapomixis in citrus and Poncirus by molecular markers. Theor ApplGenet 99(3–4):511–518. doi:10.1007/s001220051264

Georgelis N, JW S, EA B (2004) Relationship of tomato fruit sugarconcentration with physical and chemical traits and linkage ofRAPD markers. J Am Soc Hortic Sci 129(6):839–845

FG Gmitter, Jr., Grosser JW, Castle WS, Moore GA (2007) A compre-hensive citrus genetic improvement programme. Citrus Genetics,B r e ed i n g a nd B i o t e c h no l o gy : 9–18 . d o i : 1 0 . 1 079/9780851990194.0009

Gmitter Jr FG, Xiao SY, Huang S, XL H, Garnsey SM, Deng Z (1996) Alocalized linkage map of the citrus tristeza virus resistance generegion. Theor Appl Genet 92(6):688–695

Gonzalez-Jorge S, Ha S-H,Magallanes-LundbackM, Gilliland LU, ZhouA, Lipka AE, Nguyen Y-N, Angelovici R, Lin H, Cepela J, Little H,Buell CR, Gore MA, DellaPenna D (2013) Carotenoid cleavagedioxygenase4 is a negative regulator of β-carotene content inArabidopsis seeds. Plant Cell 25(12):4812–4826. doi:10.1105/tpc.113.119677

Goodner KL, Rouseff RL, Hofsommer HJ (2001) Orange, mandarin, andhybrid classification usingmultivariate statistics based on carotenoidprofiles. J Agric Food Chem 49(3):1146–1150. doi:10.1021/jf000866o

Gulsen O, Uzun A, Canan I, Seday U, Canihos E (2010) A new citruslinkage map based on SRAP, SSR, ISSR, POGP, RGA and RAPDmarkers. Euphytica 173(2):265–277. doi:10.1007/s10681-010-0146-7

Gulsen O, Uzun A, Seday U, Kafa G (2011) QTL analysis and regressionmodel for estimating fruit setting in young citrus trees based onmolecular markers. Sci Hortic 130(2):418–424. doi:10.1016/j.scienta.2011.07.010

Hodgson RW (1967) Horticultural varieties of citrus. In: Reuther W,Webber HJ, Batchelor LD (eds) The citrus industry. University ofCalifornia Division of Agricultural Sciences, Berkeley

Ikoma Y, Komatsu A, Kita M, Ogawa K, Omura M, Yano M, MoriguchiT (2001) Expression of a phytoene synthase gene and characteristiccarotenoid accumulation during citrus fruit development. PhysiolPlant 111(2):232–238. doi:10.1034/j.1399-3054.2001.1110215.x

Jansen RC, Stam P (1994) High-resolution of quantitative traits into mul-tiple loci via interval mapping. Genetics 136(4):1447–1455

Jarrell DC, Roose ML, Traugh SN, Kupper RS (1992) A genetic map ofcitrus based on the segregation of isozymes and RFLPs in an inter-generic cross. Theor Appl Genet 84(1–2):49–56

Kato M, Ikoma Y, Matsumoto H, Sugiura M, Hyodo H, Yano M (2004)Accumulation of carotenoids and expression of carotenoid biosyn-thetic genes during maturation in citrus fruit. Plant Physiol 134(2):824–837. doi:10.1104/pp.103.031104

Kijas JMH, MR T, Fowler JCS, Roose ML (1997) Integration of trinu-cleotide microsatellites into a linkage map of citrus. Theor ApplGenet 94(5):701–706. doi:10.1007/s001220050468

Lander ES, Botstein D (1989) Mapping Mendelian factors underlyingquantitative traits using RFLP linkage maps. Genetics 121(1):185–199

Lee HS (2001) Characterization of carotenoids in juice of red navel or-ange (Cara cara). J Agric Food Chem 49(5):2563–2568.doi:10.1021/jf001313g

Lee HS, Castle WS (2001) Seasonal changes of carotenoid pigments andcolor in Hamlin, Earlygold, and Budd blood orange juices. J AgricFood Chem 49(2):877–882. doi:10.1021/jf000654r

Ling P, Duncan LW, Deng Z, Dunn D, Hu X, Huang S, Gmitter Jr FG(2000) Inheritance of citrus nematode resistance and its linkage withmolecular markers. Theor Appl Genet 100(7):1010–1017

Liu Q, Xu J, Liu Y, Zhao X, Deng X, Guo L, Gu J (2007) A novel budmutation that confers abnormal patterns of lycopene accumulationin sweet orange fruit (Citrus sinensis L. Osbeck). J Exp Bot 58(15–16):4161–4171. doi:10.1093/jxb/erm273

Ma BQ, Zhao S, BH W, Wang DM, Peng Q, Owiti A, Fang T, Liao L,Ogutu C, Korban SS, Li SH, Han YP (2016) Construction of a highdensity linkage map and its application in the identification of QTLsfor soluble sugar and organic acid components in apple. Tree GenetGenomes 12(1):10. doi:10.1007/s11295-015-0959-6

Matsumoto H, Ikoma Y, Kato M, Kuniga T, Nakajima N, YoshidaT (2007) Quantification of carotenoids in citrus fruit by LC-MS and comparison of patterns of seasonal changes for ca-rotenoids among citrus varieties. J Agric Food Chem 55(6):2356–2368. doi:10.1021/jf062629c

Miyazaki T, Plotto A, Goodner K, FG G Jr (2011) Distribution of aromavolatile compounds in tangerine hybrids and proposed inheritance. JSci Food Agric 91(3):449–460. doi:10.1002/jsfa.4205

Norris SR, Barrette TR, DellaPenna D (1995) Genetic dissection of ca-rotenoid synthesis in Arabidopsis defines plastoquinone as an essen-tial component of phytoene desaturation. Plant Cell 7(12):2139–2149

Norris SR, Shen XH, DellaPenna D (1998) Complementation of theArabidopsis pds1 mutation with the gene encoding p-hydroxyphenylpyruvate dioxygenase. Plant Physiol 117(4):1317–1323. doi:10.1104/pp.117.4.1317

Ohmiya A, Kishimoto S, Aida R, Yoshioka S, Sumitomo K (2006)Carotenoid cleavage dioxygenase (CmCCD4a) contributes to whitecolor formation in chrysanthemum petals. Plant Physiol 142(3):1193–1201. doi:10.1104/pp.106.087130

de Oliveira AC, Bastianel M, Cristofani-Yaly M, do Amara AM,Machado MA (2007) Development of genetic maps of the citrusvarieties ‘Murcott’ tangor and ‘Pera’ sweet orange by using fluores-cent AFLP markers. J Appl Genet 48(3):219–231

Oliveira RPD, Cristofani M, Machado MA (2002) Genetic mapping forcitrus variegated chlorosis resistance. Laranja 23(1):247–261

Ollitrault P, Terol J, Chen C, Federici CT, Lotfy S, Hippolyte I, OllitraultF, Berard A, Chauveau A, Cuenca J, Costantino G, Kacar Y, Mu L,Garcia-Lor A, Froelicher Y, Aleza P, Boland A, Billot C, Navarro L,Luro F, Roose ML, Gmitter FG, Talon M, Brunel D (2012a) Areference genetic map of C. clementina Hort. ex Tan.; citrus evolu-tion inferences from comparative mapping. BMC Genomics 13.doi:10.1186/1471-2164-13-593

Ollitrault P, Terol J, Garcia-Lor A, Berard A, Chauveau A, Froelicher Y,Belzile C, Morillon R, Navarro L, Brunel D, Talon M (2012b) SNPmining in C. clementina BAC end sequences; transferability in thecitrus genus (Rutaceae), phylogenetic inferences and perspectivesfor genetic mapping. BMC Genomics 13. doi:10.1186/1471-2164-13-13

Raga V, Bernet GP, Carbonell EA, Asins MJ (2012) Segregation andlinkage analyses in two complex populations derived from the citrusrootstock Cleopatra mandarin. Inheritance of seed reproductivetraits. Tree Genet Genomes 8(5):1061–1071. doi:10.1007/s11295-012-0486-7

Ritter E, Gebhardt C, Salamini F (1990) Estimation of recombinationfrequencies and construction of RFLP linkage maps in plants fromcrosses between heterozygous parents. Genetics 125(3):645–654

Roose ML, Feng D, Cheng FS, Tayyar RI, Federici CT, Kupper RS(2000) Mapping the citrus genome. Acta Hortic 535:25–32

Ruiz C, Asins MJ (2003) Comparison between Poncirus and citrus ge-netic linkagemaps. Theor Appl Genet 106(5):826–836. doi:10.1007/s00122-002-1095-x

Sahin-Cevik M, Moore GA (2012) Quantitative trait loci analysis ofmorphological traits in citrus. Plant Biotechnol Rep 6(1):47–57.doi:10.1007/s11816-011-0194-z

Sankar AA,MooreGA (2001) Evaluation of inter-simple sequence repeatanalysis for mapping in citrus and extension of the genetic linkage

Tree Genetics & Genomes (2016) 12: 77 Page 15 of 16 77

map. Theor Appl Genet 102(2–3):206–214. doi:10.1007/s001220051637

Shapiro SS, Wilk MB (1965) An analysis of variance test for normality(complete samples). Biometrika 52:591–611. doi:10.2307/2333709

Sinclair WB (1984) The biochemistry and physiology of the lemon andother citrus fruits. University of California Division of Agricultureand Natural Resources, Riverside, CA

Sleper DA, Poehlman JM (2006) Breeding field crops . vol Ed. 5.Blackwell Publishing, Oxford, UK

Socquet-Juglard D, Christen D, Devenes G, Gessler C, Duffy B, PatocchiA (2013) Mapping architectural, phenological, and fruit qualityQTLs in apricot. Plant Mol Biol Report 31(2):387–397.doi:10.1007/s11105-012-0511-x

Sooriyapathirana SS, Khan A, Sebolt AM, Wang D, Bushakra JM, Lin-Wang K, Allan AC, Gardiner SE, Chagne D, Iezzoni AF (2010)QTL analysis and candidate gene mapping for skin and flesh colorin sweet cherry fruit (Prunus avium L.). Tree Genet Genomes 6(6):821–832. doi:10.1007/s11295-010-0294-x

Sugiyama A, Omura M, Matsumoto H, Shimada T, Fujii H, Endo T,Shimizu T, Nesumi H, Ikoma Y (2011) Quantitative trait loci(QTL) analysis of carotenoid content in citrus fruit. J Jpn SocHortic Sci 80(2):136–144

Sugiyama A, Omura M, Shimoda T, Fujii H, Endo T, Shimizu T, NesumiH, Nonaka K, Ikoma Y (2014) Expression quantitative trait locianalysis of carotenoid metabolism-related genes in citrus. J JpnSoc Hortic Sci 83(1):32–43

Tietel Z, Plotto A, Fallik E, Lewinsohn E, Porat R (2011) Taste and aromaof fresh and stored mandarins. J Sci Food Agric 91(1):14–23.doi:10.1002/jsfa.4146

Tozlu I, Guy CL, Moore GA (1999a) QTL analysis of morphologicaltraits in an intergeneric BC1 progeny of Citrus and Poncirus undersaline and non-saline environments. Genome 42(5):1020–1029

Tozlu I, Guy CL, Moore GA (1999b) QTL analysis of Na and Cl-accumulation related traits in an intergeneric BC1 progeny of citrusand Poncirus under saline and nonsaline environments. Genome42(4):692–705

Van Ooijen JW (2006) JoinMap 4: software for the calculation of geneticlinkage maps in experimental populations. Kyazma BV,Wageningen, Netherlands

Van Ooijen JW (2011a) MapQTL 6: software for the mapping of quan-titative trait loci in experimental populations of diploid species.Wageningen, The Netherlands

Van Ooijen JW (2011b) Multipoint maximum likelihood mapping in afull-sib family of an outbreeding species. Genet Res 93(5):343–349.doi:10.1017/s0016672311000279

Voorrips RE (2002) MapChart: software for the graphical presen-tation of linkage maps and QTLs. J Hered 93(1):77–78.doi:10.1093/jhered/93.1.77

Weber CA, Moore GA, Deng Z, Gmitter FG (2003) Mapping freezetolerance quantitative trait loci in a Citrus grandis × Poncirustrifoliata F1 pseudo-testcross using molecular markers. J Am SocHortic Sci 128(4):508–514

Wei X, Chen C, Yu Q, Gady A, Yu Y, Liang G, Gmitter Jr FG (2014)Novel expression patterns of carotenoid pathway-related genes incitrus leaves and maturing fruits. Tree Genetics & Genomes: 1–10

Wheaton TA (1997) Alternate bearing of citrus in Florida. Citrusflowering and fruiting short course. Lake Alfred: University ofFlorida, Citrus Research and Education Center: 87–92

Wu GA, Prochnik S, Jenkins J, Salse J, Hellsten U, Murat F, Perrier X,Ruiz M, Scalabrin S, Terol J, Takita MA, Labadie K, Poulain J,Couloux A, Jabbari K, Cattonaro F, Del Fabbro C, Pinosio S,Zuccolo A, Chapman J, Grimwood J, Tadeo FR, Estornell LH,Munoz-Sanz JV, Ibanez V, Herrero-Ortega A, Aleza P, Perez-PerezJ, Ramon D, Brunel D, Luro F, Chen C, Farmerie WG, Desany B,Kodira C, Mohiuddin M, Harkins T, Fredrikson K, Burns P,Lomsadze A, Borodovsky M, Reforgiato G, Freitas-Astua J,Quetier F, Navarro L, Roose M, Wincker P, Schmutz J, MorganteM, Machado MA, Talon M, Jaillon O, Ollitrault P, Gmitter F,Rokhsar D (2014) Sequencing of diverse mandarin, pummelo andorange genomes reveals complex history of admixture during citrusdomestication. Nat Biotechnol 32(7):656–662

Xu CJ, Fraser PD, Wang W-J, Bramley PM (2006) Differences inthe carotenoid content of ordinary citrus and lycopene-accumulating mutants. J Agric Food Chem 54(15):5474–5481. doi:10.1021/jf060702t

Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics136(4):1457–1468

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